Field of the Invention
This invention relates generally to a system and method for predicting whether a driver of a host vehicle or remote vehicles intends to turn at an intersection as the host vehicle is approaching the intersection and, more particularly, to a system and method for predicting whether a driver of a host vehicle or remote vehicles intends to turn at an intersection as the host vehicle is approaching the intersection, where a prediction algorithm employs a dynamic Bayesian network (DBN).
Discussion of the Related Art
Object detection systems and collision avoidance systems are becoming increasingly common on modern vehicles. Object detection systems can provide a warning to a driver about an object in the path of a moving host vehicle. The warning can be a visual indication on the vehicles instrument panel or in a head-up display (HUD), and/or can be an audio warning such as chimes or other feedback device, such as haptic seat. Object detection systems can also provide input to active vehicle systems, such as adaptive cruise control systems, which control vehicle speed to maintain the appropriate longitudinal spacing to a leading vehicle, and rear cross traffic avoidance systems, which can provide both warnings and automatic braking to avoid a collision with an object behind the host vehicle when the host vehicle is backing up.
Active safety technology employing object detection systems is currently becoming a major area of research in the automotive industry. Advances in sensor and actuator technologies have enabled the development of driver assistance systems (DAS) to prevent road accidents, especially those caused by driver mistakes or inattention. Several types of DAS, such as anti-lock braking system (ABS), electronic stability control (ESC), adaptive cruise control (ACC), lane departure warning (LDW) system, lane change assist (LCA), forward collision alert (FCA), and lane keeping assist (LKA), are already in production vehicles. Collision imminent braking is an effective way of avoiding or mitigating a collision by applying the vehicle brakes. Collision avoidance systems may also provide steering commands that cause the host vehicle to follow a calculated steering path to provide the vehicle steering to avoid a collision when braking alone can only mitigate the collision.
The object detection sensors for these types of systems may use any of a number of technologies, such as short range radar, long range radar, cameras with image processing, laser or Lidar, ultrasound, etc. The object detection sensors detect vehicles and other objects in the path of a host vehicle. In many vehicles, the object detection sensors are integrated directly into the front bumper or other fascia of the vehicle, but other mounting locations are available.
Radar and lidar sensors that may be employed on vehicles to detect objects around the vehicle and provide a range to and orientation of those objects provide reflections from the objects as multiple scan points that combine as a point cloud (cluster) range map, where a separate scan point is typically provided for every ½° across the horizontal field-of-view of the sensor. These scan points also provide a reflectivity measure of the target surface in the form of intensity in addition to the range and azimuth angle values, and therefore, if a target vehicle or other object is detected in front of the host vehicle, there may be multiple scan points that are returned that identify the surface reflectivity, distance and azimuth angle of the target vehicle from the subject vehicle. By providing a cluster of scan return points, objects having various and arbitrary shapes, such as trucks, trailers, bicycle, pedestrian, guard rail, K-barrier, etc., can be more readily detected, where the bigger and/or closer the object to the host vehicle the more scan points are provided.
Cameras on a vehicle may provide back-up assistance, take images of the vehicle driver to determine driver drowsiness or attentiveness, provide images of the road as the vehicle is traveling for collision avoidance purposes, provide structure recognition, such as roadway signs, etc. Other vehicle vision applications include vehicle lane sensing systems to sense the vehicle travel lane and drive the vehicle in the lane-center. Many of these known lane sensing systems detect lane-markers on the road for various applications, such as lane departure warning (LDW), lane keeping (LK), lane centering (LC), etc., and have typically employed a single camera, either at the front or rear of the vehicle, to provide the images that are used to detect the lane-markers.
It is also known in the art to provide a surround-view camera system on a vehicle that includes a front camera, a rear camera and left and right side cameras, where the camera system generates a top-down view of the vehicle and surrounding areas using the images from the cameras, and where the images overlap each other at the corners of the vehicle. The top-down view can be displayed for the vehicle driver to see what is surrounding the vehicle for back-up, parking, etc. Future vehicles may not employ rearview mirrors, but may instead include digital images provided by the surround view cameras.
Various vehicle systems of the type being discussed herein require that the position and orientation of the vehicle be known. Currently, modern vehicles typically rely on a global navigation satellite system (GNSS), such as GPS, that provides signals to identify vehicle location.
Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications systems, sometimes referred generally as V2X systems, are known to those skilled in the art, and require a minimum of one entity to send information to another entity. For example, many vehicle-to-vehicle safety applications can be executed on one vehicle by simply receiving broadcast messages from a neighboring vehicle. These messages are not directed to any specific vehicle, but are meant to be shared with a vehicle population to support the particular application. In these types of applications where collision avoidance is desirable, as two or more vehicles talk to each other and a collision becomes probable, the vehicle systems can warn the vehicle drivers, or possibly take evasive action for the driver, such as applying the brakes. Likewise, traffic control units can observe the broadcast of information and generate statistics on traffic flow through a given intersection or roadway.
When roadways cross intersections are created. In order to prevent vehicles from colliding with each other at an intersection, some type of traffic control mechanism, such as stop signs, yield signs, traffic lights, etc., are generally provided so that perpendicularly or cross-traveling traffic can travel safely through the intersection. However, intersections, especially high traffic intersections, are still the cause of many vehicle collisions and traffic accidents.
Known object detection sensor systems that attempt to warn the driver of a potential collision when navigating through an intersection could benefit by knowing whether the driver intends to make a turn at the intersection or drive straight through the intersection before the host vehicle reaches the intersection, and know the intent of any remote vehicles in the intersection or also approaching the intersection. Although it is impossible to exactly know the turning intent of the drivers, algorithms can be developed that identify a probability that the driver will be making a turn or traveling straight, which could be helpful.